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• RNA sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  RNA-seq for 26 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 32 samples from a previously uploaded dataset.

  Dataset EGAD50000001365

• Sequencing data for oesophageal and related samples - OACs release 2 (RNA)

  Dataset EGAD00001003839

• MEC/SEF RNA-seq

  RNA transcript expression sequencing of 27 MEC/SEF tumor samples. Samples were sequenced at Beijing Genomics Institute. Prior to sequencing, rRNA removal library preparation was done for any samples that had degraded. Samples were sequenced on a DNBseq platform sequencer with a read length of 100PE, producing approximately ~40M raw reads (~8GB) raw data per sample.

  Dataset EGAD50000000761

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• FIGHT-207: Anonymized Genomic Alterations and Clinical Responses

  Background: FIGHT-207 was a phase 2 study of the FGFR1-FGFR3 inhibitor pemigatinib in patients with previously treated, locally advanced/metastatic or unresectable solid tumor malignancies harboring activating fibroblast growth factor receptor (FGFR) gene alterations. Population information: 107 patients were divided into 3 cohorts: FGFR1–FGFR3 fusions/rearrangements; n=49 Activating FGFR1–FGFR3 non-kinase domain single nucleotide variants (SNVs); n=32 FGFR1–FGFR3 kinase domain mutations or variants of unknown significance (VUS) with potential pathogenicity; n=26 Participants on study had tumors that were grouped into the following histologies based on ≥ 5 patients: Cholangiocarcinoma, gynecologic cancers (cervical, endometrial, uterine), central nervous system (glioblastoma, low-grade pediatric glioma, astrocytoma), pancreatic cancer, breast cancer, urothelial tract/bladder cancer, non-small cell lung cancer, and other (adrenal cancer, anal cancer, cancer of unknown primary origin, colorectal cancer, gastric/gastroesophageal cancer, gallbladder cancer, giant cell bone tumor, head and neck cancer, lung neuroendocrine cancer, nasopharyngeal cancer, ovarian cancer, prostate cancer, renal cell cancer, sarcoma, solitary fibrous tumor). Among the efficacy-evaluable participants, 99 had both independent review committee (IRC) central best overall response (BOR) and tissue NGS- data; 2 additional patients had Not Evaluable (NE) as central BOR Baseline tissue targeted NGS data (F1CDx, Foundation Medicine Inc.) of genomic alterations are reported for N=101 participants Baseline plasma targeted NGS analysis (PredicineCare, Predicine Inc.) of genomic data are reported for N=83 participants; data at disease-progression are reported for N=78 participants. Principal Findings: The FIGHT-207 study provided evidence of clinical benefit of pemigatinib in multiple histologies, explored the clinical actionability of various FGFR1-FGFR3 gene alterations, and leveraged the depth of translational data from targeted NGS analysis of baseline samples and plasma samples obtained at baseline and end of treatment to provide key insights into the biology of FGFR inhibition and the clinical utility of FGFR inhibitors. The FIGHT-207 article (pending in Nat.Med. NMED-A128973B) reports evidence suggesting clinical acquired resistance to FGFR inhibition via secondary FGFR mutations as well as emerging co-mutations in other oncogenic and tumor suppressor pathways. This study also provides evidence of acquired resistance to FGFR inhibition in multiple histologies beyond cholangiocarcinoma and urothelial cancers in a systemic correlative analysis of post-progression ctDNA in a trial. Data available through dbGaP: Anonymized information for 101 participants with both IRC central BOR evaluation (including 2 patients with NE as BOR) and tissue NGS data, including tumor histology, enrollable FGFR alteration, and outcome. Genomic alterations determined by baseline tissue NGS (F1CDx, Foundation Medicine Inc.) Genomic alterations determined by plasma NGS analysis (PredicineCare, Predicine Inc.) of ctDNA analysis at baseline (n=83) and at end of treatment/ disease progression (n=78) including genomic alterations that were not assessed to be Germline SNPs.

  Study phs003590

• WES of melanoma tumors treated with combined immune checkpoint blockade

  This study of pre-treatment melanoma tumor samples from patients subsequently treated with combined anti-CTLA-4 and anti-PD-1 checkpoint blockade sought to identify genomic biomarkers of response to therapy. A total of 26 tumor and matched normal samples underwent whole exome sequencing.

  Study EGAS00001003857

• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• All you need to know about our new DAC Portal v2

  An updated version to boost the management of DACs (Data Access Committees), policies, and data access requests. In September of 2023, we launched new services for all EGA users, including a DAC Portal. Since then, our team has been working to refine it and improve the user experience. The version 2 of our DAC Portal is now ready, with a range of new features aimed at streamlining your workflow and boosting productivity. If you are interested in learning more about the latest version of our DAC Portal, then you are in the right place! In this post, you will find information about the implemented features and more. The full documentation is available on our website. Moreover, we highly recommend exploring the DAC Portal through the Take the Tour. This said, let's get cracking! Customise your data access requests table This table offers the possibility to tailor information about the data access requests by making visible or hiding different columns regarding the Dataset Persistent Identifier, the Organisation or the requestor's name s, among others. You can choose which columns to see, depending on your needs and interests. Additionally, we have implemented two new features columns with two new functionalities, DAC Comment and Expiration Date. You can find more details in the following sections! In this table, all data access requests are displayed by default. With the latest version of the Portal, you can now apply filters, combine them, and save them for future use. Leave internal comments on pending requests and visible to all the DAC Members We understand that many Data Access Committees (DACs) cannot instantly approve or deny data access requests. Often, there's an intermediary phase where discussions and the signing of legal documents are necessary. To facilitate this process, we've introduced the DAC comment feature! When you navigate to the DAC column, you'll find two tabs: "User" and "DAC". Under "User", you'll see the message provided by the requester at the time of requesting access to the data. As a DAC member/admin, you can then add an internal comment in the "DAC" tab. These comments are visible only to DAC members/admins, ensuring confidentiality. Requesters won't have access to DAC comments. By adding a DAC comment to a pending request, we'll know that you've begun reviewing it. This allows you to filter pending requests without DAC comments to focus on genuinely new requests, and it prevents you from receiving email notifications about ongoing data requests. Set expiration dates for permissions and revoke them automatically The latest update to the DAC Portal introduces a new feature allowing you to set expiration dates for new access requests. For instance, if you anticipate approving a data access request but only wish to grant access for a limited time, you can now specify an expiration date for the granted permissions. Once this date is reached, the permissions will automatically be revoked. By default, permissions are granted indefinitely without an expiration date. However, if you ever need to revoke permissions, you can easily do so from the History page. Audit your metadata objects Managing and auditing your metadata objects will be easier from now on as the new DAC Portal enhances and facilitates your role as a Data Controller. This is possible thanks to the tables available in each of the primary tabs visible on the homepage: DACs, Policies and Datasets. Starting with DACs, this section allows to check the policies linked to a specific DAC. In Policies, you can obtain a list of the datasets connected to a particular policy. In the Dataset tab, it is possible to group datasets by either DAC or Policy, as well as the release status. Now you have the option of deprecating metadata objects that you don’t want to use anymore, or that were created by mistake. You will find the deprecate button on the EDIT page of the DAC, as well as for registered policies. You can find more information here. What's neat about this feature is that once a DAC or policy is deprecated, it becomes hidden within the DAC Portal. This ensures that you only see information that is consistently up to date! Define your preferences regarding email notifications For pending requests, you will be able to decide how often you want to get the notifications: daily, weekly or fortnightly. Remember, you will not receive email notifications for pending requests with a DAC comment! Furthermore, you have the flexibility to decide which notifications you wish to receive, such as invitations to join a new DAC or notifications regarding DAC acceptance by the Helpdesk, among other options. Check the User preference to see the complete list of available notification settings! What’s next: incoming DAC Portal API In addition to the new DAC Portal, we are excited to announce the release of the DAC API! This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can consult the DAC API specification. This post was written by Aina Jené and Ana T. Alonso.

  Blog new-dac-portal-v2

• Functional characterisation of CpG islands in human tissues

  Functional characterisation of CpG islands in human tissues

  Dataset EGAD00001000212

• Colorectal adenomas, carcinomas and adjacent normal NKI-AvL TGO series NGS-ProToCol

  Cancer is caused by changes in the genome of cells, resulting in aberrant transcripts and proteins. In order to understand why normal cells become cancer cells and how we can identify and destroy them, the CTMM-NGS-ProToCol project aimed to understand prostate and colorectal cancer through DNA and RNA molecular profiling, to further improve diagnosis, prognosis and treatment.The state-of-the-art within the field of genome sequencing makes it possible to identify all the modifications in our genome that encode for RNA and of the transcripts themselves. The latest development in RNA sequencing is that if one does not select for polyA RNA, but first removes rRNA from the total RNA and then performs ‘random’ RNA sequencing, 30-60% of the reads are intronic. Since about 40% of the genome consists of genes (and only 1.6% is exonic), deep RNA sequencing will cover not only the exons, but also a large portion of the introns and therefore much of the genome. The power of the combined sequencing of genome and transcriptome is the full view of copy number aberrations (CNA), exon mutations and the consequence and relevance of the mutations at the RNA level in the form of differential gene expression, alternative splicing, alternative promoter usage, novel transcripts, fusion transcripts, read-through transcripts and mutations. For the colorectal (tumor) tissue dataset, we applied molecular profiling to 30 colorectal adenomas, 30 colorectal carcinomas and 18 normal adjacent colon tissues.

  Study EGAS00001002854